Engineers' Salary Prediction Challenge | bitgrit
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Engineers' Salary Prediction Challenge

Unlocking Engineer Salary Insights

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92 days to go
9 Participants
3 Submissions
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Brief

Are you ready to put your machine learning skills to the test? The Engineers' Salary Prediction Challenge 
is an exciting competition where participants compete to develop the most accurate salary prediction 
model for engineers in the United States.

Using a dataset with numerous variables, including job title, job description, required qualifications, 
industry, location, and experience level, your goal is to build a machine learning model that predicts 
salaries with precision. This challenge will test your ability to clean data, extract meaningful features, 
and apply predictive algorithms effectively.

This competition is a fantastic opportunity to enhance your data science skills, experiment with 
feature engineering, and compete against top ML talents.

Prizes
  • 1st Prize: $1,500
     
  • 2nd Prize: $1,000
     
  • 3rd Prize: $500
Timeline
  • Competition Starts: March 15, 2025
     
  • Competition Ends: June 15, 2025
     
  • Winners Announced (Subject to change based on submission results): June 30, 2025
Data Breakdown

Your challenge in this competition is to predict whether a job's salary falls into one of three categories: High, Medium, or Low, 
using the provided job-related data. Can you build a model that accurately classifies salaries based on factors like job title, 
description, and required qualifications? Let’s find out!

Data Breakdown:

Downloadable file "engineers_salary_prediction.zip" includes the following files:

train.csv: file to train your machine learning model.

test.csv: file that can be used to test how well your model performs on unseen data. This is the file you're going to make predictions on with your trained model and create a submission file.

solution_format.csv: example of the format that the submission file needs to be in to be properly scored.
 
<Data Dictionary>

- obs: Observation number of the data
- job_title: Anonymized job title
- job_posted_date: Year and month when the job was posted
- salary_category: The salary category (this is the target variable)
- job_state: State where the job is located
- feature_1 ~ feature_12: Various independent variables relating to job information
- job_desc_1 ~ job_desc_300: Vectorized representation of the job description

*The submission file should follow the same format as the example file (solution_format.csv). It should contain two columns: one for obs and another for salary_category. Please ensure that the salary_category column contains either "High", "Medium", or "Low" to avoid any errors. If the format is incorrect, the submission file will either return an error or yield a value of 0. Please note that submissions cannot be canceled once submitted.
**Submissions are evaluated by "Accuracy".
***Final competition results are based on the Private Leaderboard results, and the winner will be the user at the top of the Private Leaderboard.

FAQs
Who do I contact if I need help regarding a competition?
For any inquiries, please contact us at info@bitgrit.net
How will I know if I've won?
If you are one of the top three winners for this competition, we will email you with the final result and information about how to claim your reward.
How can I report a bug?
Please shoot us an email at info@bitgrit.net with details and a description of the bug you are facing, and if possible, please attach a screenshot of the bug itself.
If I win, how can I receive my reward?
Prizes will be paid by bank transfer. If for some reason you are not able to accept payment by bank transfer, please let us know and we will do our best to accommodate your needs as possible.
Rules

1. This competition is governed by the following Terms of Participation. Participants must agree to and comply with these Terms to participate.

2. Users can make a maximum number of 10 submissions per day. If users want to submit new files after making 10 submissions in a day, they will have to wait until the following day to do so. Please keep this in mind when uploading a submission file. Any attempt to circumvent stated limits will result in disqualification.

3. The use of external datasets is not allowed. (If it’s allowed, please go to the below section “Use of External datasets” to see what would be required from participants)

4. It is not allowed to upload the competition dataset to other websites. Users who do not comply with this rule will be disqualified.

5. A competition prize will be awarded after we have received, successfully executed, and confirmed the validity of both the code and the solution (See 6.). Once winners are announced and our team reaches out to them, the winners must provide the following by June 25, 2025 to be qualified as a competition winner and receive their prize:
a. All source files required to preprocess the data
b. All source files required to build, train and make predictions with the model using the processed data
c. A requirements.txt (or equivalent) file indicating all the required libraries and their versions as needed
d. A ReadMe file containing the following:
• Clear and unambiguous instructions on how to reproduce the predictions from start to finish including data pre-processing, feature extraction, model training, and predictions generation
• Environment details regarding where the model was developed and trained, including OS, memory (RAM), disk space, CPU/GPU used, and any required environment configurations required to execute the code
• Clear answers to the following questions:
- Which data files are being used?
- How are these files processed?
- What is the algorithm used and what are its main hyperparameters?
- Any other comments considered relevant to understanding and using the model

6. The submitted solution should be able to generate exactly the same output that gives the corresponding score on the leaderboard. If the score obtained from the code is different from what’s shown on the leaderboard, the new score will be used for the final rankings unless a logical explanation is provided. Please make sure to set the seed or random_state etc. so we can obtain the same result from your code. 

7. The final submission has to be selected manually before the end of the competition (you can select up to 2), or else it will be selected automatically based on your highest public score.

8. In order to be eligible for the prize, the competition winner must agree to transfer to the Host and the relevant transferee of rights in such Competition all transferable rights, such as copyrights, rights to obtain patents and know-how, etc. in and to all analysis and prediction results, reports, analysis and prediction model, algorithm, source code and documentation for the model reproducibility, etc., and the Submissions contained in the Final Submissions.

9. Any prize awards are subject to eligibility verification and compliance with these Terms of Participation. All decisions of bitgrit will be final and binding on all matters relating to this Competition.

10. Payments to winners may be subject to local, state, federal and foreign tax reporting and withholding requirements.

11. If two or more participants have the same score on the leaderboard, the participant who submitted the winning file first will be considered the winner.

12. All submissions must be made individually; no teams are allowed in this competition. Users who do not comply with this rule will be immediately disqualified in the case that we find the same or very similar scores and/or uploaded solutions.

13. If you have any inquiries about this competition, please don’t hesitate to reach out to us at info@bitgrit.net. 
 

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